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On limiting towards the boundaries of exponential families

František Matúš (2015)

Kybernetika

This work studies the standard exponential families of probability measures on Euclidean spaces that have finite supports. In such a family parameterized by means, the mean is supposed to move along a segment inside the convex support towards an endpoint on the boundary of the support. Limit behavior of several quantities related to the exponential family is described explicitly. In particular, the variance functions and information divergences are studied around the boundary.

On maximum entropy priors and a most likely likelihood in auditing.

Agustín Hernández Bastida, María del C. Martel Escobar, Francisco José Vázquez Polo (1998)

Qüestiió

There are two basic questions auditors and accountants must consider when developing test and estimation applications using Bayes' Theorem: What prior probability function should be used and what likelihood function should be used. In this paper we propose to use a maximum entropy prior probability function MEP with the most likely likelihood function MLL in the Quasi-Bayesian QB model introduced by McCray (1984). It is defined on an adequate parameter. Thus procedure only needs an expected value...

On maximum likelihood estimation in mixed normal models with two variance components

Mariusz Grządziel (2014)

Discussiones Mathematicae Probability and Statistics

In the paper we deal with the problem of parameter estimation in the linear normal mixed model with two variance components. We present solutions to the problem of finding the global maximizer of the likelihood function and to the problem of finding the global maximizer of the REML likelihood function in this model.

On measures of concordance.

Marco Scarsini (1984)

Stochastica

We give a general definition of concordance and a set of axioms for measures of concordance. We then consider a family of measures satisfying these axioms. We compare our results with known results, in the discrete case.

On metric divergences of probability measures

Igor Vajda (2009)

Kybernetika

Standard properties of φ -divergences of probability measures are widely applied in various areas of information processing. Among the desirable supplementary properties facilitating employment of mathematical methods is the metricity of φ -divergences, or the metricity of their powers. This paper extends the previously known family of φ -divergences with these properties. The extension consists of a continuum of φ -divergences which are squared metric distances and which are mostly new but include...

On Mieshalkin-Rogozin theorem and some properties of the second kind beta distribution

Włodzimierz Krysicki (2000)

Discussiones Mathematicae Probability and Statistics

The decomposition of the r.v. X with the beta second kind distribution in the form of finite (formula (9), Theorem 1) and infinity products (formula (17), Theorem 2 and form (21), Theorem 3) are presented. Next applying Mieshalkin - Rogozin theorem we receive the estimation of the difference of two c.d.f. F(x) and G(x) when sup|f(t) - g(t)| is known, improving the result of Gnedenko - Kolmogorov (formulae (23) and (24)).

On minimax sequential procedures for exponential families of stochastic processes

Ryszard Magiera (1998)

Applicationes Mathematicae

The problem of finding minimax sequential estimation procedures for stochastic processes is considered. It is assumed that in addition to the loss associated with the error of estimation a cost of observing the process is incurred. A class of minimax sequential procedures is derived explicitly for a one-parameter exponential family of stochastic processes. The minimax sequential procedures are presented in some special models, in particular, for estimating a parameter of exponential families of...

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